Mid- sagittal slice showing tracing of the whole corpus callosum.

<p>Mid- sagittal slice showing tracing of the whole corpus callosum.</p

Intra-class correlations (ICC) estimates for MZ and DZ twin groups for whole CC DTI measures.

<p><u>Notes:</u> MZ – monozygotic twins; DZ- Dizygotic twins; FA – Fractional anisotropy; MD- Mean diffusivity; RD- radial diffusivity; AD – Axial diffusivity; ICC- Intra-class correlations.</p><p>Intra-class correlations (ICC) estimates for MZ and DZ twin groups for whole CC DTI measures.</p

Descriptive Statistics for the DTI measures.

<p><u>Notes</u>: FA – Fractional anisotropy; MD- Mean diffusivity; RD- Radial diffusivity; AD – Axial diffusivity; SD – standard deviation; CC – corpus callosum. The means are calculated considering all the voxels within that subregion^a.</p><p>Descriptive Statistics for the DTI measures.</p

Demographics and Characteristics of the Twin Sample.

<p><u>Notes:</u> MZ – monozygotic twins; DZ- Dizygotic twins; M –mean; SD – standard deviation.</p><p>Demographics and Characteristics of the Twin Sample.</p

Heritability estimates for Whole CC and its five sub-regions [A-E] for the four DTI measures.

<p>*Values are significant at p<.0001.</p><p><u>Notes</u>: FA – Fractional anisotropy; MD- Mean diffusivity; RD- radial diffusivity; AD – Axial diffusivity; h²- heritability estimate; SE – standard error.</p><p>Heritability estimates for Whole CC and its five sub-regions [A-E] for the four DTI measures.</p

Mid- sagittal slice showing the divisions of corpus callosum into 5 regions anterior to posterior (A–E) using the parcellation method of Chao et al. [39].

<p>Mid- sagittal slice showing the divisions of corpus callosum into 5 regions anterior to posterior (A–E) using the parcellation method of Chao et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0113181#pone.0113181-Chao1" target="_blank">[39]</a>.</p

Sample characteristics.

<p>MIC-1/GDF15 = Macrophage Inhibitory Cytokine—1 / Growth Differentiation Factor 15</p><p>CRP = C-Reactive Protein</p><p>IL-6 = Interleukin-6</p><p>SD = standard deviation</p><p>^a 247 participants received both MRI scans and blood tests at both Waves.</p><p>^b The number of subjects varied among different measures due to missing data</p><p>^c Cardiovascular disease (CVD) risk scores were calculated based on Framingham Heart Disease Risk Score, which was a percentage illustrating the summary of cardiovascular risks of age, sex, systolic blood pressure, use of antihypertensive treatment, cigarette smoking, diabetes mellitus, total cholesterol, high-density lipoprotein (HDL) cholesterol, and body mass index (BMI). The score ranged from 7 to 28 at wave 1, and 7 to 26 at wave 2.</p><p>^d The data came from self-report</p><p>Sample characteristics.</p

The moderation analysis model.

<p>A graphical illustration of the moderation analysis of whether the initial MIC-1/GDF15 serum levels at Wave 1 moderated the strength of the associations between changes in MIC-1/GDF15 serum levels and GM volumes.</p

Vertex-based analyses of associations between Macrophage Inhibitory Cytokine—1 (MIC-1/GDF15) serum levels and cortical volume at Wave 1.

<p>The result was adjusted for age, sex, years of education, scanner, and intracranial volume (ICV) (Model 1). The results were corrected at a false discovery rate (FDR) of 0.05 and projected onto a semi-inflated brain. Negative correlations are indicated by cyan and blue, and positive correlations by red and yellow.</p

Regression analyses for the associations between Wave 1 GM volumes and changes in MIC-1/GDF15 serum levels.

<p>Model 1: adjusting for age, sex, years of education, scanner, and ICV</p><p>Model 2: adjusting for confounders after model reduction using stepwise procedure. The full confounder list includes history of CVA, TIA, AMI, angina, cancer, APOE4 genotype, race, CVD risk scores, CRP level, and IL-6 level.</p><p>Regression analyses for the associations between Wave 1 GM volumes and changes in MIC-1/GDF15 serum levels.</p